Triple
T19351454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russell Casse |
E484028
|
entity |
| Predicate | deathSceneQuote |
P135533
|
FINISHED |
| Object | "Hello, boys! I'm back!" |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: "Hello, boys! I'm back!" | Statement: [Russell Casse, deathSceneQuote, "Hello, boys! I'm back!"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deathSceneQuote Context triple: [Russell Casse, deathSceneQuote, "Hello, boys! I'm back!"]
-
A.
deathSceneWork
Indicates that a creative work features or depicts the scene in which a character dies.
-
B.
deathDescribedAs
Indicates that one entity characterizes, portrays, or refers to another entity’s death using a particular description, metaphor, or wording.
-
C.
deathInterpretedAs
Indicates that one entity’s death is understood, framed, or interpreted in a particular way by another entity or within a given context.
-
D.
deathEpisode
Indicates the episode or event in which an entity’s death occurs or is depicted.
-
E.
deathLeadsTo
Indicates that one entity’s death causes, results in, or brings about another event, state, or condition.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8e8d244f8819080eb1f3491300db2 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e61904a878819084d58ed3b7d8a978 |
completed | April 20, 2026, 12:16 p.m. |
| PD | Predicate disambiguation | batch_69e4dd12303c8190a2027c062b2dff40 |
completed | April 19, 2026, 1:48 p.m. |
| PDg | Predicate description generation | batch_69e4df51ac6c819091ce72b07790ffa6 |
completed | April 19, 2026, 1:57 p.m. |
Created at: April 10, 2026, 1:34 p.m.